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1 Degenhardt, L., Peacock, A., Colledge, S., Leung, J., Grebely, J., Vickerman, P.,... Larney, S. (2017). Global prevalence of injecting drug use and sociodemographic characteristics and prevalence of HIV, HBV, and HCV in people who inject drugs: a multistage systematic review. Lancet Global Health, 5(12), e1192-e1207. DOI: /S X(17) Publisher's PDF, also known as Version of record License (if available): CC BY-NC-ND Link to published version (if available): /S X(17) Link to publication record in Explore Bristol Research PDF-document University of Bristol - Explore Bristol Research General rights This document is made available in accordance with publisher policies. Please cite only the published version using the reference above. Full terms of use are available:

2 Global prevalence of injecting drug use and sociodemographic characteristics and prevalence of HIV, HBV, and HCV in people who inject drugs: a multistage systematic review Louisa Degenhardt, Amy Peacock, Samantha Colledge, Janni Leung, Jason Grebely, Peter Vickerman, Jack Stone, Evan B Cunningham, Adam Trickey, Kostyantyn Dumchev, Michael Lynskey, Paul Griffiths, Richard P Mattick, Matthew Hickman*, Sarah Larney* Summary Background Sharing of equipment used for injecting drug use (IDU) is a substantial cause of disease burden and a contributor to blood-borne virus transmission. We did a global multistage systematic review to identify the prevalence of IDU among people aged years; sociodemographic characteristics of and risk factors for people who inject drugs (PWID); and the prevalence of HIV, hepatitis C virus (HCV), and hepatitis B virus (HBV) among PWID. Methods Consistent with the GATHER and PRISMA guidelines and without language restrictions, we systematically searched peer-reviewed databases (MEDLINE, Embase, and PsycINFO; articles published since 2008, latest searches in June, 2017), searched the grey literature (websites and databases, searches between April and August, 2016), and disseminated data requests to international experts and agencies (requests sent in October, 2016). We searched for data on IDU prevalence, characteristics of PWID, including gender, age, and sociodemographic and risk characteristics, and the prevalence of HIV, HCV, and HBV among PWID. Eligible data on prevalence of IDU, HIV antibody, HBsAg, and HCV antibody among PWID were selected and, where multiple estimates were available, pooled for each country via random effects meta-analysis. So too were data on percentage of PWID who were female; younger than 25 years; recently homeless; ever arrested; ever incarcerated; who had recently engaged in sex work, sexual risk, or injecting risk; and whose main drugs injected were opioids or stimulants. We generated regional and global estimates in line with previous global reviews. Findings We reviewed papers and reports, and extracted data from 1147 records. Evidence of IDU was recorded in 179 of 206 countries or territories, which cover 99% of the population aged years, an increase of 31 countries (mostly in sub-saharan Africa and the Pacific Islands) since a review in IDU prevalence estimates were identified in 83 countries. We estimate that there are 15 6 million (95% uncertainty interval [UI] million) PWID aged years globally, with 3 2 million ( million) women and 12 5 million ( million) men. Gender composition varied by location: women were estimated to comprise 30 0% (95% UI ) of PWID in North America and 33 4% ( ) in Australasia, compared with 3 1% ( ) in south Asia. Globally, we estimate that 17 8% ( ) of PWID are living with HIV, 52 3% ( ) are HCV-antibody positive, and 9 0% ( ) are HBV surface antigen positive; there is substantial geographic variation in these levels. Globally, we estimate 82 9% ( ) of PWID mainly inject opioids and 33 0% ( ) mainly inject stimulants. We estimate that 27 9% ( ) of PWID globally are younger than 25 years, 21 7% ( ) had recently (within the past year) experienced homelessness or unstable housing, and 57 9% ( ) had a history of incarceration. Interpretation We identified evidence of IDU in more countries than in 2008, with the new countries largely consisting of low-income and middle-income countries in Africa. Across all countries, a substantial number of PWID are living with HIV and HCV and are exposed to multiple adverse risk environments that increase health harms. Funding Australian National Drug and Alcohol Research Centre, Australian National Health and Medical Research Council, Open Society Foundation, World Health Organization, the Global Fund, and UNAIDS. Copyright The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 license. Lancet Glob Health 2017 Published Online October 23, S X(17) See Online/Articles S X(17)30373-X *Joint senior authors National Drug and Alcohol Research Centre, UNSW Sydney, Sydney, NSW, Australia (Prof L Degenhardt PhD, A Peacock PhD, S Colledge BPsychSc[Hons], Prof R P Mattick PhD, S Larney PhD); School of Public Health, Faculty of Medicine, University of Queensland, Herston, QLD, Australia (J Leung PhD); Kirby Institute, UNSW Sydney, Sydney, NSW, Australia (J Grebely PhD, E B Cunningham BSc[Hons]); Population Health Science, Bristol Medical School, University of Bristol, Bristol, UK (Prof P Vickerman PhD, J Stone MMathStat, A Trickey MSc, Prof M Hickman PhD); Ukrainian Institute for Public Health Policy, Kiev, Ukraine (K Dumchev MD); National Addiction Centre, King s College London, London, UK (Prof M Lynskey PhD); and European Monitoring Centre on Drugs and Drug Addiction, Lisbon, Portugal (P Griffiths MSc) Correspondence to: Prof Louisa Degenhardt, National Drug and Alcohol Research Centre, UNSW Sydney, Sydney, NSW 2052, Australia l.degenhardt@unsw.edu.au Introduction Sharing of equipment used for injecting drug use (IDU) causes substantial disease burden. Transmission via contaminated injection paraphernalia of blood-borne viruses, including HIV, hepatitis C virus (HCV), and hepatitis B virus (HBV), is a leading contributor to morbidity and mortality as a consequence of IDU. 1 Quantification of the size of the population of people who inject drugs (PWID), their demographic characteristics, and the extent of their exposure to risk behaviours and environments is essential to enable effective health policy planning. 2 5 In and, for hepatitis, 2011, 7 we did systematic reviews to estimate the prevalence of IDU globally and Published online October 23,

3 Research in context Evidence before this study In 2008 and 2011, global systematic reviews were done to estimate the prevalence of injecting drug use (IDU) globally, as well as the prevalence of HIV, hepatitis C virus (HCV), and hepatitis B virus (HBV) among people who inject drugs (PWID). These reviews noted an increase in the number of countries where IDU had been identified relative to a review from Although annual updates are produced by agencies such as the UN Office on Drugs and Crime (UNODC) and the European Monitoring Centre on Drugs and Drug Addiction (EMCDDA), these focus on a limited number of countries (EMCDDA), rely on member state reporting (UNODC), and do not involve systematic reviews of evidence. These estimates do not adhere to the Guidelines for Accurate and Transparent Health Estimates Reporting (GATHER). Studies suggest that experience of homelessness, arrest, imprisonment, and sex work can increase exposure of PWID to HIV, HCV, and HBV, and increase risks of health harm. Age, gender, and the types of drugs injected affect exposure to blood-borne virus risk and might require quite different treatment and harm reduction responses. To our knowledge, there has never been a global review of these issues among PWID. Added value of this study In the past decade, surveillance capacity has been enhanced across many low-income and middle-income countries. Targets for reductions in HIV and viral hepatitis due to IDU have been developed, and drug dependence treatment coverage has been listed as one of the UN Sustainable Development Goals, making updates of previous estimates crucially important. This Article updates estimates of the number of PWID at the country level, regional level, and global level by use of a multi-stage systematic review of peer-reviewed and grey literature, data reported by government and other agencies, and expert consultation. To our knowledge, our work represents the first global review of sociodemographic characteristics of and risk factors for PWID, and we present the first estimates of IDU by gender at the country, regional, and global level. We also summarise evidence on PWID, including their experience of incarceration, sex work, and homelessness. Implications of all the available evidence IDU has now been documented in most countries and territories in the world, and HIV and HCV infection are prevalent in many populations of PWID, representing a substantial challenge to public health. There is a clear mandate to invest in blood-borne virus prevention activities such as needle and syringe programmes and opioid substitution therapy, and to provide treatment and care for those who are living with HIV and HCV. Importantly, our results highlight the consistently high levels of exposure to significant risk factors faced by PWID across countries. These risk factors include those about which there might be less capacity for individual control, emphasising the clear need to address structural and environmental drivers of vulnerability, risk, and harm. See Online for appendix the prevalence of HIV, HCV, and HBV among PWID. These reviews generated new evidence, documented an increase in the number of countries where IDU had been recorded relative to a review 10 years earlier, 8 and identified gaps and shortcomings in the available data (for example, we identified many countries where no studies had been done with PWID). This Article updates these previous estimates. During the past decade, surveillance capacity has been enhanced in many countries, including Global Fund support for studies of and services for PWID across multiple lowincome and middle-income countries. Patterns of drug use have shifted globally, including increasing pharmaceutical opioid use and injection in some countries and changes in amphetamine and coca derivatives in some regions. 9 Targets for reductions in HIV and viral hepatitis infection have been developed, 10,11 and drug dependence treatment coverage has been listed as one of the UN s Sustainable Development Goals. 12 All of these factors make updating of previous estimates crucially important. Experience of homelessness, 13 arrest, 14 incarceration, 15,16 and sex work 17 can increase exposure of PWID to HIV, HCV, and HBV, and increase their risks of physical and mental health harms. Age, 18 gender, 19 and the types of drugs injected are associated with blood-borne virus risk among PWID, and could require quite different treatment and harm reduction responses. We aimed to update the estimates of the number of PWID at country, regional, and global levels. This Article also represents the first global review of sociodemographic characteristics of and risk factors for PWID. At the country, regional, and global level, we examined the number of countries with evidence of IDU and estimates of the number of PWID; the prevalence of HIV, HBV, and HCV among PWID; and the characteristics of PWID and patterns of drug use and risk history, including exposure to homelessness, arrest, incarceration, and sex work. Methods Search strategy and selection criteria This study was a global, multistage systematic review of peer-reviewed and grey literature. The methods used were consistent with previous global reviews 6,7 and in accordance with the PRISMA 23 and GATHER 24 guidelines (appendix pp 3 5). The protocols were registered on PROSPERO, numbers CRD and CRD Our search strategy had several stages, as in previous reviews. 6,7 We did not limit the searches by language. 2 Published online October 23,

4 We searched electronic peer-reviewed literature databases (MEDLINE, Embase, and PsycINFO) using a comprehensive set of search terms developed in consultation with a specialist drug and alcohol librarian (appendix pp 6 10). We limited the searches to studies published since Jan 1, 2008, or since Jan 1, 2011 for hepatitis (ie, from the year of the previously published reviews). We did the searches in April, 2016, and updated them in June, Any systematic reviews with potentially relevant sources that were identified were hand-searched for relevant papers or reports. We searched grey literature and online databases that we had identified as sources of papers or reports on IDU and blood-borne viruses 25 via their own search function or Google advanced search between April and June, 2016, limiting our search to records published since Jan 1, 2008 (or Jan 1, 2011, for hepatitis). These sources included the websites of drug surveillance systems, regional harm reduction networks, and country-specific ministries of health. We updated our methods to identify and systematically search grey literature for this review 25 and the sites searched are detailed in the appendix (pp 11 60). Between April and August, 2016, we searched key documents by relevant international agencies, including the UN Office on Drugs and Crime s (UNODC) World Drug Reports, 9 Harm Reduction International s Global State of Harm Reduction reports, 26 and reports from the European Monitoring Centre on Drugs and Drug Addiction (EMCDDA), WHO, UNAIDS, and Global Fund. We updated the searches between May and June, We contacted members of these organisations directly to obtain data when additional information was required. We also sought data via expert requests. We requested data on the epidemiology of IDU and blood-borne viruses in October, 2016, via an distribution process and social media. This process consisted of initial s sent to more than 2000 key experts and organisations, including contacts in the global, regional, and country offices of WHO, UNAIDS, Global Fund, and UNODC (appendix p 61). Staff in those agencies also forwarded the request to their colleagues and other relevant contacts. One member of the research team (SL) posted a request for data on Twitter, which was delivered to 5525 individual feeds (appendix p 62). Screening and extraction We created an Endnote (version X.8) library to catalogue papers and reports and remove duplicates. References were screened by three researchers (LD, SL, and AP), assisted by researchers at the National Drug and Alcohol Research Centre, University of New South Wales (UNSW); the Kirby Institute UNSW; the University of Queensland; the University of Bristol; and the Ukrainian Institute on Public Health Policy. The research team had members proficient in reading sources written in English, Panel: Decision rules for data extraction and estimation processes Overall Estimates with sample sizes 40 PWID were excluded Samples which represented a subpopulation (eg, prisoners, all HIV positive or HIV negative) were excluded, as were those with 15% or more missing data (eg, due to incomplete responding or attrition in follow-up) Where multiple sources were identified with data from the same sample, the sources with the most complete data regarding the various indicators of interest were included Where possible, if calculation or typesetting errors were detected in reported estimates, these were recalculated or clarified with authors Prevalence of injecting drug use Where multiple estimates were available, higher grade estimates (grading classifications are detailed in the appendix p 62) were selected in preference to other grades Geographic coverage was preferred over recency of an estimate an older national estimate was used in preference to a newer estimate that focused only on one city or region; this rule recognises that, especially in large countries (eg, India), there can be considerable regional variation in IDU prevalence Estimates of current PWID defined as those who had injected in the past 12 months were selected in preference to estimates for PWID defined by other criteria; other estimates were included in the absence of the preferred definition; the definition of injecting drug use for each estimate is noted in the findings When deriving the prevalence of injecting drug use, it was also assumed that PWID were aged between 15 and 64 years of age HIV, hepatitis C, and hepatitis B among PWID City, subnational, and national estimates (grade A C) published within the last 4 years of the most recently available estimate were pooled where multiple estimates were available for a country For sentinel surveillance, if no details were provided on whether a single or multiple sample types were used, it was assumed that only a single sample type was used and graded C Estimates based on case notifications, self-report, or unspecified methodologies were excluded Studies that excluded PWID according to sex (eg, those actively excluding female PWID) were not included if mixed gender studies were available Characteristics of PWID All data for each country were pooled where multiple estimates were available Estimates were excluded if the sample inclusion or exclusion criteria reflected the characteristic of interest (eg, samples where participation was restricted to male PWID were excluded from meta-analyses of the percentage female) Where categorical data for age were available, we calculated the percentage who were young, defined where possible as 24 years In the case of time-varying indicators (eg, injecting risk behaviours), estimates for recent timeframes (ie, 12 months) were pooled A range of risk behaviours could occur around injecting drug use; we chose to extract data on receptive needle-syringe sharing (ie, using a needle after someone else) Similarly, a range of behaviours could confer risk during sexual activity; we focused on extracting estimates of unprotected sex (ie, sex without a condom) We also extracted data from surveys of PWID who reported what the main drug was that they injected; in some instances we could not locate any studies assessing this, but surveys in a country reported last drug injected ; or if not last drug injected, whether they had recently injected in these instances (appendix) we used those estimates Full details are available in the appendix (pp 67, 68). PWID=people who inject drugs. Published online October 23,

5 IDU search HBV and HCV search HIV search Initial search peer-reviewed 1565 PsycINFO 9792 Embase 5035 MEDLINE excluded 3721 duplicate by title 8173 grey-literature 7898 excluded by title 4709 peer-reviewed 458 PsycINFO 2995 Embase 1256 MEDLINE 3980 excluded 1085 duplicate 2895 by title 8173 grey-literature 7914 excluded by title peer-reviewed 1741 PsycINFO 5395 Embase 3841 MEDLINE excluded 3466 duplicate 6557 by title 8173 grey-literature 7709 excluded by title Screen and eligibility 1489 reviewed by 1054 excluded by 275 reviewed by 232 excluded by 729 reviewed by 538 excluded by 259 reviewed by 244 excluded by 954 reviewed by 751 excluded by 464 reviewed by 426 excluded by 435 peer-reviewed 43 grey-literature 191 peer-reviewed 15 grey-literature 203 peer-reviewed 38 grey-literature Supplementary search Included Expert consultation Screen and eligibility 5759 supplementary citations 5045 hand search 204 Global Fund 71 EMCDDA 187 UNAIDS 173 UNODC WDR 79 GSHR 531 supplementary citations 98 hand search 108 Global Fund 71 EMCDDA 2 UNAIDS 173 UNODC WDR 79 GSHR 61 expert consultation citations 21 expert citations 1030 compiled in IDU review 5228 not 4947 hand search 96 Global Fund 0 EMCDDA 185 UNAIDS 0 UNODC WDR 0 GSHR 40 not 54 redundant 5766 supplementary citations 5045 hand search 204 Global Fund 211 EMCDDA 268 UNODC WDR 38 GSHR 582 supplementary citations 65 hand search 30 Global Fund 181 EMCDDA 268 UNODC WDR 38 GSHR 14 expert citations 5184 not 4980 hand search 174 Global Fund 30 EMCDDA 0 UNODC WDR 0 GSHR 61 expert consultation citations 61 expert consultation citations 802 compiled in hepatitis review 47 not Final inclusion 1147 unique sources with data extracted for reviews on IDU, HBV and HCV, and HIV 562 peer-reviewed articles 56 grey-literature documents 91 hand search 115 Global Fund 349 EMCDDA 15 UNAIDS 36 expert citations 14 expert citations 1004 compiled in HIV review 3146 not 2875 hand search 122 Global Fund 19 EMCDDA 130 UNAIDS 0 UNODC WDR 0 GSHR 385 redundant 402 redundant 976 included in IDU review 417 included in hepatitis review 602 included in HIV review 3895 supplementary citations 2953 hand search 204 Global Fund 258 EMCDDA 187 UNAIDS 187 UNODC WDR 106 GSHR 749 supplementary citations 78 hand search 82 Global Fund 239 EMCDDA 57 UNAIDS 187 UNODC WDR 106 GSHR 47 not 4 Published online October 23,

6 French, Spanish, Portuguese, Hebrew, Bahasa Malaysian, Russian, Ukrainian, and Chinese languages. Other non- English language data sources were read via Google Translate or the Microsoft Word translate function. Initial screening of title and abstract was done independently by one reviewer with a random 10% check by another (LD, SL, or AP), with no discrepancies found. Screened references were selected for review if the title or abstract suggested that the document might contain relevant information (panel; appendix pp 63 68). Full-text review was also independently done by two authors (LD, SL, or AP), with discrepancies resolved by consensus except for fewer than 30 records, for which a third reviewer was consulted (MH; consensus was reached in all instances). 67 authors were contacted to request fulltext where that was unavailable (eg, if only an abstract was presented) or to provide details of the methods or results. Data from studies were extracted into a purpose-built database in Microsoft Access We extracted data at all levels reported in the study, including city, subnational, and country. Data were then checked for accuracy against the original source by one of three authors (LD, SL, or AP). All extracted data were categorised by country: we included all UN Member States, as well as countries or territories for which IDU has been reported, or where we identified evidence that an intervention for PWID was being implemented. 27 We extracted data on studies estimating the prevalence of IDU. From studies of PWID, we extracted data on sociodemographic characteristics and risk variables (gender, age, unstable housing or homelessness, recent incarceration, arrest, and recent involvement in sex work), patterns of drug use and risk (recent injecting risk, sexual risk, and types of drugs injected), HIVantibody prevalence, HCV-antibody prevalence (previous exposure) and reports of HCV-RNA prevalence (active infection), and HBV surface antigen (HBsAg) prevalence (active infection). Data analysis Our data analysis approach was informed by methods used in earlier reviews 6,7 (panel; appendix pp 63 68). On the basis of the extracted data, we made initial calculations of country-level prevalence estimates in accordance with a classification system and a set of decision rules (panel; appendix pp 63 71). Estimates were generated by one member of the research team (SC or LD), and independently reviewed by at least two others (LD, AP, JL, or SL); any discrepancies were resolved with discussion and consultation (SC, LD, AP, SL, JL). External checks Figure 1: Flowchart presenting number of sources from identification to inclusion UNODC WDR=UN Office on Drugs and Crime s World Drug Report. GSHR=HRI s Global State of Harm Reduction. EMCDDA=European Monitoring Centre on Drugs and Drug Addiction. HBV=hepatitis B virus. HCV=hepatitis C virus. IDU=injecting drug use. were made with specific requests to experts in countries where additional data or clarification of identified data were needed. JG did a third independent check once estimates had been selected and pooled. All authors also finally reviewed all selected estimates. Estimates of the prevalence of IDU were graded by quality (appendix pp 63, 64), and higher-grade estimates were selected over lower-grade estimates; we also aimed to maximise geographic coverage of estimates within a country. If two or more estimates of the same quality grade were identified, these were pooled via randomeffects meta-analysis. The proportions were pooled across studies within a given country via random-effects metaanalyses in Stata version 14 by use of the metaprop command. Metaprop allows meta-analyses of proportions for binomial data. The CIs were calculated with the exact method based on the binomial distribution. If no estimate of IDU prevalence was located of the same or higher quality since the previous review, 6 the estimate from the previous review was used again. Eligible data on the prevalence of HIV antibody, HBsAg, and HCV antibody among PWID were selected and, where multiple estimates were available, pooled for each country (decision rules around selection of estimates are shown in the appendix pp 65, 66). On the basis of these extracted data, we made initial calculations of countrylevel prevalence estimates in accordance with agreed decision rules around the selection of estimates, approaches to pooling estimates within-country (panel), and determination of uncertainty intervals (UIs) around estimates. Estimates were pooled via random-effects models. To estimate the number of PWID with bloodborne virus infections (HIV antibody, HBsAg, and HCV antibody) among the country population sizes, we multiplied IDU prevalence by the proportion of each blood-borne virus variable among PWID. We then multiplied this product by the size of the country population aged years to obtain number of PWID with blood-borne viruses. 95% UIs were estimated with Monte Carlo simulation taking draws. We used a binomial distribution because our parameters of interest were proportions (product of IDU proportion among population and blood-borne virus proportion among PWID). Estimated sample sizes were derived on the basis of the 95% CIs and standard errors of the proportion estimates in each country. The simulated UIs incorporated the uncertainty of both IDU and bloodborne virus estimates. Following the collation of country-specific estimates, regional and global IDU, HIV, and viral hepatitis estimates were derived. Regional groupings were based on those used by UNAIDS, WHO, and UNODC. We made region-specific, weighted estimates of the prevalence of HIV, HCV, HBV, and IDU using all the observed estimates and 95% CIs of estimates in each country within that region and deriving a weighted estimate and UIs, taking into account country population For the EMCDDA archive see data/stats Published online October 23,

7 Number of countries Number of people aged years (millions)* People who inject drugs HIV among people who inject drugs HCV among people who inject drugs HBV among people who inject drugs Countries with evidence of IDU Population with evidence of IDU* Countries with IDU prevalence estimates Population with IDU prevalence estimates* Countries with prevalence of HIV Population of PWID with HIV prevalence estimates Countries with prevalence of anti-hcv Population of PWID with HCV prevalence estimates Countries with prevalence of HBsAg Population of PWID with HBsAg prevalence estimates Eastern Europe Western Europe East and southeast Asia % 100% % 87% % 100% % 100% % 99% >99% >99% % 97% % 98% % >99% % 84% % 99% % 95% % 94% % 98% % 82% South Asia % 100% % >99% % >99% % 99% % 99% Central % 100% % 92% % 92% % 92% % 26% Asia Caribbean % 65% % 9% % 9% 0 1 0% 9% 0 0 0% 0% Latin >99% >99% % 68% % 81% % 75% % 44% America North % 100% % 100% % 100% % 100% % 90% America Pacific % >99% 0 0 0% 0% 3 3 8% 7% 0 0 0% 0% 0 0 0% 0% Island States and Territories Australasia % 100% % 100% % 100% % 100% % 100% Sub % 97% % 36% % 56% % 42% % 35% Saharan Africa Middle % 98% 2 3 2% 9% % 80% % 63% % 54% East and north Africa Global % 99% % 82% % 90% % 88% % 76% IDU=injecting drug use. HCV=hepatitis C virus. HBV=hepatitis B virus. Anti-HCV=HCV antibodies. HBsAg=hepatitis B surface antigen. *Percentage of general population aged years for whom an estimate of the prevalence of injecting drug use had been identified in that region or globally. Percentage of the estimated population of people who inject drugs in that region or globally for whom an HIV, HCV, or HBV prevalence estimate was available. The number of countries in western Europe and the global total differs from that of the earlier reviews 6,7 in that the UK (previously presented as one jurisdiction) is now presented separately as England, Northern Ireland, Scotland, and Wales; Croatia and Greenland are included in western Europe; the Northern Mariana Islands are included in the Pacific Island States and Territories; and South Sudan is presented as a separate country. Table 1: Countries with evidence on injecting drug use and HIV, anti-hcv, and HBsAg prevalence among people who inject drugs 6 Published online October 23,

8 size. We used UN Population Division estimates of country population size (age years). 28 We then used regional estimates to estimate the global prevalence (appendix pp 69, 70). Although few prevalence estimates of IDU present gender-specific estimates, this information is crucial for service planning. We estimated the number of women (and men) who inject drugs by extracting all available data in each country on the percentage of PWID samples who were female. We pooled these proportions across studies within a given country via random-effects metaanalyses in Stata version 14 using the metaprop command. To estimate the number of female PWID, we multiplied the proportion of women among PWID by the prevalence of IDU, then by the population size of the country. We calculated population-level prevalence of IDU for women and men using UN population estimates for men and women aged years in each country. 28 For pooling percentages of PWID across studies with data for sociodemographic characteristics and risk factors, we pooled all estimates of each characteristic for a country via random-effects meta-analyses in Stata version 14 using the metaprop command. We calculated the CIs using the exact method based on the binomial distribution. We report pooled estimates of the percentage of PWID who were young (age <25 years at the time of interview), had unstable housing or were homeless (current or past year), had a lifetime experience of police arrest, had a lifetime history of incarceration, and had recently engaged in sex work (current or past year among all PWID in a sample, not by gender). We also report pooled estimates of the percentage of PWID who had recently engaged in injecting risk behaviour (predominantly receptive needle sharing, typically in the past month) and pooled estimates of the percentage of PWID who recently engaged in sexual risk behaviour (predominantly no or inconsistent condom use with casual partner, typically within the past month). We also extracted data on the reported main drug for injection; we report the percentage of PWID across countries whose main drug for injection was either an opioid (heroin or other opioid) or stimulant (amphetamine or cocaine). Further details of this process, including definitions and decision rules around selection of estimates for inclusion in these pooled estimates, are provided in the panel and appendix (pp 67, 68). Role of the funding source The funders of the study had no role in study design, data collection, data analysis, data interpretation, or writing of the report. The corresponding author had full access to all the data in the study and had final responsibility for the decision to submit for publication. Results We screened records, consisting of peerreviewed publications across the three searches (IDU, All Women Men Estimated number of PWID (95% UI) Population prevalence of IDU (95% UI) Estimated number of PWID (95% UI) Population prevalence of IDU (95% UI) Estimated number of PWID (95% UI) PWID who are women* (95% UI) Population prevalence of IDU (95% UI) Eastern Europe 1 30% ( ) ( ) 25 4% ( ) 0 64% ( ) ( ) 2 00% ( ) ( ) Western Europe 0 34% ( ) ( ) 28 6% ( ) 0 20% ( ) ( ) 0 49% ( ) ( ) East and southeast 0 25% ( ) ( ) 20 8% ( ) 0 10% ( ) ( ) 0 40% ( ) ( ) Asia South Asia 0 09% ( ) ( ) 3 1% ( ) 0 01% ( ) ( ) 0 16% ( ) ( ) Central Asia 0 63% ( ) ( ) 12 6% ( ) 0 16% ( ) ( ) 1 13% ( ) ( ) Caribbean 0 44% ( ) ( ) 11 1% ( ) 0 16% ( ) ( ) 0 74% ( ) ( ) Latin America 0 46% ( ) ( ) 13 0% ( ) 0 12% ( ) ( ) 0 81% ( ) ( ) North America 1 06% ( ) ( ) 30 0% ( ) 0 63% ( ) ( ) 1 49% ( ) ( ) Pacific Island States 0 33% ( ) ( ) 22 1% ( ) 0 15% ( ) 5000 ( ) 0 51% ( ) ( ) and Territories Australasia 0 59% ( ) ( ) 33 4% ( ) 0 39% ( ) ( ) 0 78% ( ) ( ) Sub-Saharan Africa 0 28% ( ) ( ) 11 6% ( ) 0 06% ( ) ( ) 0 49% ( ) ( ) Middle East and 0 12% ( ) ( ) 3 5% ( ) 0 01% ( ) ( ) 0 22% ( ) ( ) north Africa Global 0 33% ( ) ( ) 22 1% ( ) 0 13 ( ) ( ) 0 52% ( ) ( ) Numbers are rounded to the nearest 500. Estimates are for people aged years. Country-level estimates of IDU prevalence are available in the appendix. IDU=injecting drug use. PWID=people who inject drugs. UI=uncertainty interval. *The country-level pooled estimates of the percentage of PWID who are women, which informed these regional estimates, are presented in the appendix. No estimates of the prevalence of injecting drug use could be located for the Pacific Island States and Territories, so we used the weighted observed global prevalence here; we also did not locate any studies of people who inject drugs in these countries, so the observed global weighted percentage of PWID who are women was used in estimating the number of male and female PWID considerable caution should be used in the interpretation of these estimates. Table 2: Estimates of the prevalence of injecting drug use and number of people who inject drugs, by gender Published online October 23,

9 HBV and HCV, and HIV), 8173 grey literature reports from websites listed in the appendix (pp 11 60), and, in our supplementary search, papers or reports from international organisations or from hand searches of 85 reviews that we identified as relevant. We received an additional 61 papers or reports from experts. Across these search stages, 1147 records were ultimately for at least one aspect of our review (figure 1). As of June 5, 2017, evidence of IDU was reported in 179 of 206 countries or territories; these countries hold 99% of the world s population aged years (table 1). This is an increase of 31 countries since the previous review of IDU prevalence. 6 The additional countries were mostly in sub-saharan Africa (n=23) and four Pacific Island States and Territories. The number of studies estimating IDU prevalence also increased, with an additional 22 countries now having an estimate of IDU prevalence since the previous review (nine of these in sub-saharan Africa; table 1), such that 83 countries (containing 82% of world population aged years) now have an estimate of IDU prevalence. We also noted increases in the number of countries with studies quantifying the prevalence of HIV, HCV, and HBV infection among PWID (table 1). The region with the largest number of countries with new data was sub-saharan Africa, which had new studies of HIV in 12 countries, HCV in six countries, and HBV in four countries. The Middle East and north Africa also had increases in the number of countries with studies (four on HIV, three on HCV, and two on HBV). Globally, in 2015 an estimated 15 6 million people (95% UI million) injected drugs, amounting to approximately 0 33% ( ) of those aged years (table 2; detailed country estimates are given in the appendix (pp 72 78). We estimated that 3 2 million ( million) women inject drugs globally. At a regional level, prevalence varied from 0 09% (95% UI ) in south Asia to 1 30% ( ) in eastern Europe (table 2). The largest populations of PWID were in east and southeast Asia (4 0 million, million), eastern Europe (3 0 million, million), and North America (2 6 million, million). The percentage of PWID who were women varied substantially across regions (table 2). We estimated that women represented 30 0% (95% UI ) of PWID in North America and 33 4% ( ) in Australasia, compared with 3 1% ( ) among PWID in south Asia. The prevalence of IDU among men was far higher than in women in all regions. We noted substantial variation in the estimated countrylevel prevalence of IDU (figure 2); country estimates and further details are available in the appendix (pp 72 78). Georgia and Seychelles had the highest estimates for IDU prevalence; however, Russia, the USA, and China contributed the largest proportions of the total IDU No evidence of IDU IDU evidence, no estimate >0 00% to <0 25% 0 25% to <0 50% 0 50% to <1% 1 00% Figure 2: Estimated prevalence of injecting drug use by country IDU=injecting drug use. 8 Published online October 23,

10 HIV HCV HBV Prevalence among PWID (95% UI) Estimated number of PWID living with HIV (95% UI) Prevalence among PWID (95% UI) Estimated number of PWID who are HCV-antibody positive (95% UI) Prevalence among PWID (95% UI) Estimated number of PWID who are HBsAg positive (95% UI) Eastern Europe 24 7% ( ) ( ) 64 7% ( ) ( ) 7 9% ( ) ( ) Western Europe 4 5% ( ) ( ) 53 2% ( ) ( ) 3 2% ( ) ( ) East and 15 2% ( ) ( ) 50 3% ( ) ( ) 19 8% ( ) ( ) southeast Asia South Asia 19 4% ( ) ( ) 38 6% ( ) ( ) 5 7% ( ) ( ) Central Asia 10 5% ( ) ( ) 54 0% ( ) ( ) 9 3% ( ) ( ) Caribbean 13 5% ( ) ( ) 63 6% ( ) ( ) 10 2% ( ) ( ) Latin America 35 7% ( ) ( ) 61 9% ( ) ( ) 2 8% ( ) ( ) North America 9 0% ( ) ( ) 55 2% ( ) ( ) 4 8% ( ) ( ) Pacific Island 16 3% ( ) ( ) 55 5% ( ) ( ) 10 2% ( ) ( ) States and Territories* Australasia 1 1% ( ) ( ) 57 1% ( ) ( ) 3 6% ( ) ( ) Sub-Saharan 18 3% ( ) ( ) 21 8% ( ) ( ) 3 7% ( ) ( ) Africa Middle East and 3 6% ( ) ( ) 48 1% ( ) ( ) 8 1% ( ) ( ) north Africa Global 17 8% ( ) ( ) 52 3% ( ) ( ) 9 0 % ( ) ( ) Country-level estimates of IDU prevalence are available in the appendix (pp 71 76; details of country-level estimates of HIV, HBV, and HCV are in the appendix pp ). Numbers are rounded to the nearest 500. IDU=injecting drug use. PWID=people who inject drugs. HCV=hepatitis C virus. HBV=hepatitis B virus. Anti-HCV=HCV antibodies. HBsAg=hepatitis B surface antigen. *No estimates of the prevalence of HIV, anti-hcv or HBsAg could be located for the Pacific Island States and Territories, so we used the weighted observed global prevalence considerable caution should be used in the interpretation of these estimates. Table 3: Regional and global estimates of people who inject drugs who are HIV positive, anti-hbc positive, and HBsAg positive No evidence of IDU No report <5% 5% to <10% 10% to <20% 20% to <40% 40% Figure 3: Estimated HIV prevalence among people who inject drugs by country IDU=injecting drug use. No report=evidence of IDU located, but no study of HIV prevalence among people who inject drugs that met our eligibility criteria was located. Published online October 23,

11 population. We estimated much lower prevalence for countries in Asia and sub-saharan Africa than in other regions, with some exceptions, for example Seychelles and Malaysia. Globally, we estimate that 2 8 million (95% UI million) PWID are living with HIV, amounting to 17 8% ( ) of PWID (table 3). HIV prevalence among PWID varied substantially across geographical regions, from 1 1% ( ) in Australasia, 3 6% ( ) in the Middle East and north Africa, and 4 5% ( ) in western Europe, to 24 7% ( ) in eastern Europe and 35 7% ( ) in Latin America. We estimate that eastern Europe and Latin America have the largest numbers of PWID living with HIV. The prevalence of HIV among PWID varied widely across countries even within regions, as shown in figure 3 (country estimates and details are presented in the appendix pp 79 91). For example, in eastern Europe, HIV prevalence estimates ranged from 0 01% in Slovakia to 53 4% in Estonia, while in western Europe, estimates ranged from 0% in Serbia to 32 6% in Spain. Globally we estimated that 52 3% (95% UI ) of current PWID have been exposed to hepatitis C (anti- HCV positive), equating to 8 2 million ( million) people. Only 21 countries had studies with data on HCV-RNA prevalence. In most regions and countries, more than half of PWID have been infected with HCV. We estimated that PWID in sub-saharan Africa had a lower prevalence of anti-hcv (21 8%, ) compared with regions where IDU has been established for longer. We estimated higher anti-hcv prevalence in some countries in east and southeast Asia (eg, Indonesia, Taiwan, Thailand), although the regional estimated prevalence was lower, largely because HCV-antibody prevalence among PWID in China was estimated to be lower (figure 4; country estimates and details are provided in the appendix pp ). We estimated that 9 0% (95% UI ) of PWID have chronic HBV infection (HBsAg positive), equating to 1 4 million ( million) people. The region (table 3) with the highest estimated HBsAg prevalence among PWID was east and southeast Asia, although countries with the highest prevalence also included the Czech Republic, Egypt, Belarus, Lithuania, the Côte d Ivoire, and Azerbaijan (figure 5; country estimates and details are provided in the appendix pp ). We estimated that PWID in east and southeast Asia represent more than half of all HBsAg-positive PWID worldwide (table 3). Regional estimates of the characteristics of populations of PWID are presented in table 4 (country-level estimates and source references for all pooled estimates are available in the appendix pp ). We found substantial geographic variation in the age of PWID. No evidence of IDU No report <40% 40% to <60% 60% to <80% 80% Figure 4: Estimated anti-hepatitis C virus prevalence among people who inject drugs by country IDU=injecting drug use. No report=evidence of IDU located, but no study of HCV antibody prevalence among people who inject drugs that met our eligibility criteria was located Published online October 23,

12 The proportion of young PWID (age <25 years) was lower in countries from Australasia (14 9%, range ) and North America (15 3%, ), and much higher in countries from Latin America (51 2%, %). The lowest proportions of young PWID were in the Caribbean and central Asia, although estimates in these regions were only based on one country each (Puerto Rico and Kyrgyzstan, respectively). The extent of exposure to risk also varied substantially. Exposure of PWID to recent homelessness or unstable housing ranged from 6 7% (range ) in eastern Europe to 50 3% ( ) in North America. History of incarceration ranged from 35 7% ( ) in eastern Europe to 82 4% ( ) in Puerto Rico, the only country in the Caribbean for which estimates could be calculated, and recent involvement with sex work ranged from 3 3% ( ) in the Caribbean (ie, Puerto Rico) to 21 3% ( ) in North America. The extent of engagement in injecting and sexual risk behaviours varied widely among samples of PWID across countries. The proportion reporting recent injecting risk (using shared needles or syringes) was much higher in Latin America (54 0%, range ) and central Asia (46 8%, ), and lowest in western Europe (10 2%, ). The highest rates of recent sexual risk (ie, unprotected sex) were in sub-saharan Africa (47 5%, ), the Middle East and north Africa (40 1%, ), western Europe (38 0%, ), and eastern Europe (37 7%, ), whereas the lowest proportion was in Australasia (10 7%, ). Opioids were typically the main drug injected (table 4). The country with the lowest percentage of PWID reporting opioids as their main drug was the Czech Republic (21 6%, range ; appendix pp ). Higher proportions of PWID had stimulants as their main injected drug in countries in North America, eastern Europe, and Australasia (table 4). The pooled percentages of opioids and stimulants could exceed 100% because different studies could be included in the opioid versus stimulant pooled estimates, and in some countries, PWID reported that a combination of opioid and stimulants (eg, so-called speedballs) was their main drug injected. The number of estimates and quality grading for each country is shown in the appendix (pp ), for IDU prevalence and HIV, HCV-antibody, and HBsAg prevalence among PWID. Overall, 237 of 343 countrylevel estimates were based on evidence from grade A or B study methods, and 20 country-level estimates represented pooled data across multiple grade estimates, which included C grade estimates. If we restricted IDU prevalence estimates to grade A or B only (ie, indirect prevalence estimation studies and household surveys only), the global estimated prevalence of PWID would be slightly lower than our main calculation, at 0 27% No evidence of IDU No report <2% 2% to <5% 5% to <10% 10% Figure 5: Estimated hepatitis B virus surface antigen prevalence among people who inject drugs by country IDU=injecting drug use. No report=evidence of IDU located, but no study of hepatitis B surface antigen prevalence among people who inject drugs that met our eligibility criteria was located. Published online October 23,